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Record W2041644768 · doi:10.1063/1.4869656

Nanostructure evolution in joining of Al and Fe nanoparticles with femtosecond laser irradiation

2014· article· en· W2041644768 on OpenAlexaff
Zhen Jiao, Hong Huang, Li Liu, Anming Hu, W. W. Duley, Peigang He, Y. Zhou

Bibliographic record

VenueJournal of Applied Physics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceNanoparticleTransmission electron microscopyNanostructureAmorphous solidLaser ablationFemtosecondIrradiationCrystalliteLaserElectron diffractionNanotechnologyChemical engineeringCrystallographyAnalytical Chemistry (journal)DiffractionOpticsMetallurgyChemistry

Abstract

fetched live from OpenAlex

The joining of Al-Fe nanoparticles (NPs) by femtosecond (fs) laser irradiation is reported in this paper. Fe and Al NPs were deposited on a carbon film in vacuum via fs laser ablation. Particles were then exposed to multiple fs laser pulses at fluences between 0.5 and 1.3 mJ/cm2. Transmission Electron Microscopy (TEM) and Electron Diffraction X-ray observations indicate that Al and Fe NPs bond to each other under these conditions. For comparison, bonding of Al to Al and Fe to Fe NPs was also investigated. The nanostructure, as observed using TEM, showed that individual Al NPs were monocrystalline while individual Fe NPs were polycrystalline prior to joining and that these structures are retained after the formation of Al-Al and Fe-Fe NPs. Al-Fe NPs produced by fs laser joining exhibited a mixed amorphous and crystalline phase at the interface. Bonding is suggested to originate from intermixing within a region of high field intensity between particles.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.220
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2014
Admission routes1
Has abstractyes

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